With thousands of distinctively different sounding rock songs produced up to now, the genre of rock music has reinvented itself over the decades. To participate in the never-ending evolution of rock music, we decided to explore the use of AI to generate uniquely new rock songs using GPT-2 for lyrics generation and TeleMelody for melody generation.

pip install spotipy
pip install lyricsgenius

Run .ipynb files Here

The lyrics generation step requires a csv file containing a single column with rows of different song lyrics, and the gpt2 pre-trained model which can be downloaded using the command gpt_2_simple.download_gpt2(model_name="124M").

The training data we used to fine-tune the GPT-2 model can be downloaded here, along with a fine-tuned checkpoint file.

To fine-tune a model, call the GPT2_lyrics_train.py file in the command line and provide the path to the csv file.

python GPT2_lyrics_train.py "<file path>"

Some useful fine-tuning model parameters:

• model_name: locally downloaded pre-trained model
• learning_rate: tuning parameter for the step size at each iteration
• optimizer: either 'adam' or 'sgd'
• batch_size: number of samples for each iteration
• steps: number of iterations to train
• sample_every: generate samples every n steps
• sample_length: print text with n tokens
• save_every: write a checkpoint every n steps
• print_every: print training progress
• restore_from: either "fresh" to start training from the default pre-trained model or "latest" to continue training from a checkpoint file
• run_name: fine-tuned model name

This will create a checkpoint for this fine-tuned model which can be used during the lyrics generation step.

The lyrics can be generated by calling the GPT2_lyrics_generate.py file in the command line and provide the path to the fine-tuned checkpoint folder.

python GPT2_lyrics_generate.py "<checkpoint folder path>"

Some useful parameters to generate lyrics:

• temperature: higher temperature the model gives more random text generations (default=0.85)
• top_p: cumulative probability to control the number of word guesses (default=0.9)
• top_k: top k number of words to guess from when generating (default=0 i.e. disabled feature)
• length: number of tokens to generate (default=200. max token allowed is 1023)

!pip install phonemizer
!sudo apt-get install espeak-ng
!sudo apt-get install festival

Preprocessing the lyrics requires for the lyrics to be in the most basic level of speech, which is a phoneme. The combination of phonemes create words.

! mkdir data/

From Phonemization import get_phones
get_phones('lyrics.txt')

• Obtain lyrics2rhythm Checkpoints from checkpoint_best.pt
• Obtain Template2melody Checkpoints from checkpoint_best.pt

Place each checkpoint in its respective folder, and remove placeholder checkpoint in ----> Input checkpoints Here

Input lyrics.txt file & syllables.txt into this repository Edit Chord Progression at discretion

! cd Lyric-Melody-Generation/Lyric-to-Melody/
! python infer_en.py lyric2rhythm template2melody test output